Many of us develop our algorithm and simulate it using Matlab environment where there are many built-in functions available for any applications. If your job is just to do proof-of-concept simulation, you need to just learn about Matlab programming technique.

However, if you need to do more than just simulation and if you need to implement the algorithm into any hardware or embedded target, you need to go beyond Matlab environment. You need to use Simulink environment to develop your algorithm, simulate it and implement it on your hardware. There are many type of supported hardware that can work with Simulink. At this present time, Matlab hardware support is still limited. Therefore, Simulink is the best choice that we have at the moment.

Below is the example of simple Sobel Edge detection algorithm that run on Raspberry Pi hardware. The result that you get from simulation is the same as the result that you get from the hardware.

To understand the workflow on working with Raspberry Pi hardware for Image Processing, you can attend “Exploring Image Processing with Matlab, Simulink and Raspberry Pi” on 15-17 October 2014.